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Shannon entropy in time-varying semantic networks of titles of scientific paper

机译:Shannon熵在时变的科学论文标题的语义网络

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Recent work has employed information theory in social and complex networks. Studies often discuss entropy in the degree distributions of a network. However, no specific work on entropy exists in clique networks. This work is an extension of a previous study that discussed this topic. We propose a method for calculating the entropy of a clique network and its minimum and maximum values in temporal semantic networks based on titles of scientific papers. In addition, the critical network of moments was extracted. We use the titles of scientific papers published in Nature and Science over ten-year period. The results show the diversity of vocabulary over time, based on the entropy values of vertices and edges. In each critical network, we discover the paths that connect important words and an interesting modular structure.
机译:最近的工作在社会和复杂网络中使用了信息理论。研究经常讨论网络的程度分布中的熵。但是,CLIQUE网络中没有关于熵的具体工作。这项工作是讨论此主题的前一项研究的延伸。我们提出了一种基于科学论文标题计算Clique网络熵的方法及其在时间语义网络中的最小值和最大值。此外,提取了临界时刻网络。我们在十年期间使用本质上发表的科学论文的标题。结果基于顶点和边缘的熵值显示了随着时间的推移的多样性。在每个关键网络中,我们发现连接重要单词和有趣的模块结构的路径。

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